Choosing Transport Events for Initiating Splitting and Rouletting †

Evan S. Gonzalez, Gregory G. Davidson

    Research output: Contribution to journalArticlepeer-review

    2 Scopus citations

    Abstract

    A study was performed to determine which transport events should be used to initiate a weight window lookup to achieve the best variance reduction performance. A weight window lookup potentially triggers particle splitting (in important regions of phase space) or rouletting (in unimportant regions), thereby optimizing computational effort. Potential initiating transport events include collisions (both pre- and post-collision), geometry surface crossings, traversing a mean-free path, and streaming across a weight window boundary. Permutations of these initiating events were tested on an urban model with background radiation sources and a spent fuel cask with a neutron dose mesh tally. Generally, all methods perform better with finer weight window meshes. Tracking on weight windows performs well for coarse weight window meshes, while a combination of splitting each mean-free path, geometric surface crossing, and before collisions performs well for fine weight window meshes.

    Original languageEnglish
    Pages (from-to)97-104
    Number of pages8
    JournalJournal of Nuclear Engineering
    Volume2
    Issue number2
    DOIs
    StatePublished - Jun 2021

    Funding

    Work for this paper was supported by ORNL, which is managed and operated by UT-Battelle LLC, for the US Department of Energy under Contract No. DEAC05-00OR22725. This work was sponsored by the US Nuclear Regulatory Commission under task order NRC-HQ-60-17-T-0027 and was performed under the Nuclear Engineering Science Laboratory Synthesis (NESLS) program at ORNL. This work was also sponsored by the Enabling Capabilities for Nonproliferation and Arms Control Program Area of the Office of Defense Nuclear Nonproliferation Research and Development, National Nuclear Security Administration.

    Keywords

    • FW-CADIS
    • Monte Carlo
    • shift
    • variance reduction

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